Healthcare

This paper investigates the effectiveness of formalized collaboration strategies through which patients can be transferred and resources, including staff, equipment and supplies, can be shared across hospitals in response to a disaster incident involving mass casualties and area-wide damage. Inflicted damage can affect hospital infrastructure and its supporting lifelines, thus impacting capacity and capability or, ultimately, services that are provided. Using a discrete event simulation framework and underlying open queuing network conceptualization involving patient flows through 9 critical units of each hospital, impacts on critical resources, physical spaces and demand are modeled and the hospital system's resilience to these hazard events is evaluated. Findings from numerical experiments on a case study involving multiple hospitals spaced over a large metropolitan region replicating a system similar to the Johns Hopkins Hospital System show the potential of strategies involving not only transfers and resource sharing, but also joint capacity enhancement alternatives to improve post-disaster emergency health care service delivery through joint action.

Discrete event simulation is one of the key technologies to assist in the development of a flexible and agile production system in this Industry 4.0 era. An ExtendSim model was built for an AstraZeneca production system containing five production lines. Using the model to understand the behavior and analyze the production lines identified that the production lines were not efficient and were being underutilized, as the company assumed. It further helped identify possible improvements while evaluating the feasibility of the production system to achieve the forecasted demand over time.

This study builds on earlier research which focuses on the use of combined simulation methods to support healthcare demand predictions. The authors developed a hybrid simulation model composed of two submodels which were built using different simulation paradigms. Both models, i.e. a population model based on a continuous modeling approach and an arrivals model built with discrete-event methodology, were created in ExtendSim. This combined model simulates the consequences of demographic changes, the variability in incidence rates that result from an aging population, and the seasonal fluctuations in epidemic trends on future demand for healthcare services.

This presentation outlines the story of a Medical Device Fortune 500 company’s experience in implementing a combined simulation and optimization solution not integrated to the primary ERP system of a critical manufacturing location. You'll learn about the pros and cons, and the challenges and lessons learned, during the implementation process using a discrete simulation model using OpStat methodology launched in two critical areas in 2015 and 2016. After a weekly simulation and optimization process was enacted, customer service rose to unprecedented levels, while plant financial performance became enterprise benchmarks. The process knowledge acquired by the team during the implementation also resulted in a major shift in the nature of the work of the planning organization, evolving from a group of schedulers to a team of holistic capacity planners. To accomplish this task in an evidence-based way, a simulation model was developed using ExtendSim. This approach helped the clinical, managerial, and facility staff to not just understand their existing department workflow but also to provide them the opportunity to test trans-disciplinary scenarios to guide the design of the new emergency department. Furthermore it provided the client with the statistics to evaluate the impact a new Chest Pain & General Observation Center and Results Waiting Lounge would have on their entire system.

On a cool Saturday morning Dr. Keith Weems walked briskly down the hallway toward the main entrance to Eastern Hospital (JHH). He was on his way to visit in-patients in several wards as part of his duties as the pain specialist on call for that weekend. However, his mind kept drifting to issues he was facing as the new manager of the Miller Pain Treatment Center in the neighboring Eastern Outpatient Center (E-HOC). Dr. Weems had been working as part of the Eastern system for several years. However, he recently merged his successful private practice into the Miller Pain Treatment Center and was appointed as its director. In so doing he moved from a setting where he was the clear boss to one in which he was dealing with a collection of more established doctors already set in their ways. He also had to figure out how to improve the care delivery process in this environment, which considered itself to be part of the premier teaching hospital in the world. After reviewing the operations and meeting the staff he was coming to grips with the fact that this new setting was much more complex than his old practice in a myriad of ways. Additionally, between treating outpatients and in-patients, managing the clinic, teaching medical students, and conducting research, it was clear that the complexity of the job mirrored the complexity of the operating environment. However, he was confident that he could find ways to get this larger clinic to surpass the success of his old, simpler practice.

The existing hospital system is struggling with the current volume of patients. The predicted increase in volume will push the existing system past its breaking point. Our team was tasked with not only designing a new emergency department with the appropriate capacity, but more importantly seeing how various operational changes would affect the new system while investigating clinical trends and the effect on the whole hospital system.

To accomplish this task in an evidence-based way, a simulation model was developed using ExtendSim. This approach helped the clinical, managerial, and facility staff to not just understand their existing department workflow but also to provide them the opportunity to test trans-disciplinary scenarios to guide the design of the new emergency department. Furthermore it provided the client with the statistics to evaluate the impact a new Chest Pain & General Observation Center and Results Waiting Lounge would have on their entire system.

This report presents an integrated simulation-based approach to study the on-site production of concrete frameworks by considering the multiple effects of weather on work task productivity and concrete curing process. The ExtendSim model created reports simulated construction time, cost, and CO₂ emissions for a specific construction setup to facilitate planning and decisions related to resource allocation strategies, construction schedules, different concrete types (including climate-improved concrete), and curing measures for different types of expected weather conditions.

Architecture and operations are inherently linked. What happens inside a building is influenced by space, and space is influenced by what goes on inside of it. This is especially important in health care architecture and design. Health care programmers, planners and designers have always regarded operations planning in some capacity during the architectural process but how this is done has evolved.

Here the authors discuss three project examples where both spreadsheet analysis and/or Six Sigma simulation were used during pre-design to plan and improve operations performance in health care settings.

Given the complexity of the emerging National Healthcare Information Network (NHIN) and Service Oriented Architectures (SOAs) due to multiple levels of system interactions, creating a valid and usable SoSE model for SOA application using a single technique that captures the desired level of details can be a daunting task. This paper details a hybrid approach to the modeling and simulation of a specific SOA that has been configured for potential defense applications, then adapted to healthcare. This system could also be used to allow connecting slow-speed remote telemedicine tools without violating the HIPAA Confidentiality, Security, and Availability requirements.

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses’ role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

A simulation model can guide the team through a more efficient planning process and will offer solutions that are not static. These dynamic solutions mirror the changing climate of health care, offering opportunities to predict the impact of future changes in clinical care, operations, and architecture in the ICU.

This paper presents a comprehensive exploration of an Internal Medicine outpatient clinic practice setting by applying a discrete event simulation (DES) model. Growing demands on outpatient clinics require greater emphasis on enhancing performance and optimizing resource utilization. Therefore, a data collection plan was designed to capture total patient visit time; including waiting, clinical care, and clinical administrative time. The collected data was fed into a DES model. The mode was validated through a statistical comparison with the performance of the real system. Various improvement alternatives were then proposed and investigated through the DES model, such as altering resource allocation, patient rooming and prioritization, and patient volume. For each scenario, key performance indicators of the system, resource utilization metrics, capacity metics, and turnaround time metrics were traced. Findings indicated that targeted improvement scenarios could be applied with 27.5%, 54.8%, and 20% enhancement in utilization, capacity, and turnaround time respectively.

Explores the potential of discrete event simulation (DES) methods to advance system-level investigation of emergency department (ED) operations. To this end, the authors describe the development and operation of Emergency Department SIMulation (EDSIM), a new platform for computer simulation of ED activity at a Level 1 trauma center. The authors also demonstrate one potential application of EDSIM by using simulated ED activity to compare two patient triage methods.

The Leeds & Wakefield Breast Screening Service & Primary Care Trusts (part of National Health Service in the UK) saved buying at least 2 new breast cancer screening machines.

Healthcare architecture design of a new ambulatory surgery unit explores the relationship between the number of operating rooms and recovery beds, the number of cases and the phases of recovery, bed capacity, staffing, and waiting room seat requirements as each affected the design. Model results allowed time for variations in the design to meet the client's needs before the project was built. Furthermore, the simulation shows the positive outcome of combining the experience of three professional disciplines: healthcare planning, architecture, and simulation modeling for nurses, doctors and patients of the new ambulatory surgery unit.

Simulation modeling is a tool of hospital-wide system process change with a focus on improving patient satisfaction through a better clinical process. Some of the improvements, based on existing systems, include decreased delays, better healthcare staff utilization and tailored scheduling. In this part 2 of 2 perioperative case studies (part 1: Ambulatory Surgery Unit), the experiences of three distinct, yet complimentary professions are combined and opitimized: nursing/healthcare planning, architecture, and simulation engineering to create a better way to provide a clinical service in a newly designed healthcare space.

The US Army uses Combat Support Hospitals (CSHs)—mobile, deployable hospitals housed in tents and expandable containers—to provide surgical and trauma care close to combat action. CSHs provide the highest level of in-theater medical care available to American military personnel serving in active, deployed operations, including stabilization and surgical capabilities comparable to those in the trauma centers of major hospitals in the United States.

RAND Corporation took on a project for the Army to develop and evaluate alternative strategies for equipping the CSHs to meet their equipment and maintenance needs.Using ExtendSim to evaluate the performance of alternative equipping strategies for CSHs, the study identified a new equipment and maintenance strategy that has the potential to enable the Army to reduce the cost of equipment and maintain its CSHs at fully modernized levels, providing them with equipment that is newer and in better condition on average than what they had prior to the study.

A large hospital in southeast United States utilized simulation to aid project leaders in advancing to the next level of sophistication with Six Sigma. The ExtendSim model brought clarity to potential process improvements in their Emergency Department (ED) and enabled the hospital to test design ideas of a planned new facility.

Consultants used ExtendSim to find new ways of designing processes that achieve better patient flow, deliver greater care, are supported by staff, and provide better value-for-money for the delivery of mental health services in South Tyneside. The resulting PatientFlow plans and the simulation are being used very succesfully to build and deploy their ‘dream team’ of therapists in a way that can meet the 50% increase in referrals within approved headcount and budget.

Emergency management planners and health care facilities are faced with potential scenarios that may severely test their capabilities and conventional processes. This paper presents the development of a simulation-based environment that allows emergency planners and professionals to prepare more robust emergency response plans without using costly, time consuming physical drills.

The ExtendSim model built for this project could be used to

• analyze the effects of incoming calls on a system.
• optimize personnel resources at call centers.
• investigate the impact of workload distribution, shift schedule adjustments, and staffing profiles on response times.
• estimate the impact on the resources required in relation to a reduction or increase in the number of communication centers.
• improve the efficiency and location of dispatch services.
• improve the ambulance allocation algorithm.

What began as an MBA class project at Purdue University’s Krannert School of Management is now applying factory management techniques to a medical clinic, ultimately improving productivity and quality. With their help, the clinic was able to serve 37 percent more patients on a given day.